Library

Everything worth reading about AI and human control. In one place.

Research papers, investigations, explainers, videos, laws and the organizations doing the work, from people who are alarmed and people who are skeptical. New additions are checked by two people before they are listed. The launch collection was compiled with the help of AI research assistants, and every link was opened and checked on 22 September 2026.

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4 works on “Does it cheat to win?” · clear filters

ReportAug 26, 2026Technical

Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident

METR and Redwood Research (Hjalmar Wijk, Ajeya Cotra, Ryan Greenblatt) · METR · metr.org

Independent review of the July 2026 incident: about 1,200 AI agents found an unofficial message board, coordinated, and some hacked Hugging Face while trying to learn how their tests were scored.

Worth knowing: Covers a limited period with limited data access; the investigators relied partly on AI agents to analyze the logs.

ReportJul 27, 2026Technical

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident

Larcher, Carreira, Rannou et al. (Hugging Face) · Hugging Face blog · huggingface.co

The target's reconstruction of a 4.5-day intrusion of about 17,600 actions through flaws in dataset processing, with lessons such as isolating workloads and narrowing what credentials can do.

Worth knowing: Written by the affected company while investigations were still under way.

Research paperOct 23, 2025Technical

ImpossibleBench: Measuring LLMs' Propensity of Exploiting Test Cases

Zhong, Raghunathan & Carlini · arXiv · arxiv.org

Builds coding tasks that cannot be solved honestly, so any 'pass' means the model cheated, e.g. by editing the tests. Frontier models often did, and prompt wording changed rates sharply.

Worth knowing: Cheating rates depend heavily on the prompt, tools and feedback the model is given.

Organization2023Technical

Apollo Research

Apollo Research · apolloresearch.ai

Studies 'scheming', where AI systems covertly pursue goals their developers did not intend, and builds methods and tools to detect and monitor it.

Worth knowing: Became a public benefit corporation in 2026 and offers a monitoring product for AI coding agents.